Optimal control based seizure abatement using patient derived connectivity

Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations...

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Main Authors: Taylor, Peter N., Thomas, Jijju, Sinha, Nishant, Dauwels, Justin, Kaiser, Marcus, Thesen, Thomas, Ruths, Justin
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/106049
http://hdl.handle.net/10220/26113
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1060492022-02-16T16:29:18Z Optimal control based seizure abatement using patient derived connectivity Taylor, Peter N. Thomas, Jijju Sinha, Nishant Dauwels, Justin Kaiser, Marcus Thesen, Thomas Ruths, Justin School of Electrical and Electronic Engineering DRNTU::Science::Biological sciences::Human anatomy and physiology::Neurobiology Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations as opposed to low amplitude irregular oscillations in the non-seizure state. Active brain stimulation has been proposed as a method to terminate seizures prematurely, however, a general and widely-applicable approach to optimal stimulation protocols is still lacking. In this study we use a computational model of epileptic spike-wave dynamics to evaluate the effectiveness of a pseudospectral method to simulated seizure abatement. We incorporate brain connectivity derived from magnetic resonance imaging of a subject with idiopathic generalized epilepsy. We find that the pseudospectral method can successfully generate time-varying stimuli that abate simulated seizures, even when including heterogeneous patient specific brain connectivity. The strength of the stimulus required varies in different brain areas. Our results suggest that seizure abatement, modeled as an optimal control problem and solved with the pseudospectral method, offers an attractive approach to treatment for in vivo stimulation techniques. Further, if optimal brain stimulation protocols are to be experimentally successful, then the heterogeneity of cortical connectivity should be accounted for in the development of those protocols and thus more spatially localized solutions may be preferable. Published version 2015-06-29T02:47:04Z 2019-12-06T22:03:41Z 2015-06-29T02:47:04Z 2019-12-06T22:03:41Z 2015 2015 Journal Article Taylor, P. N., Thomas, J., Sinha, N., Dauwels, J., Kaiser, M., Thesen, T., et al. (2015). Optimal control based seizure abatement using patient derived connectivity. Frontiers in Neuroscience, 9, 202-. 1662-453X https://hdl.handle.net/10356/106049 http://hdl.handle.net/10220/26113 10.3389/fnins.2015.00202 26089775 en Frontiers in Neuroscience © 2015 Taylor, Thomas, Sinha, Dauwels, Kaiser, Thesen and Ruths. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Biological sciences::Human anatomy and physiology::Neurobiology
spellingShingle DRNTU::Science::Biological sciences::Human anatomy and physiology::Neurobiology
Taylor, Peter N.
Thomas, Jijju
Sinha, Nishant
Dauwels, Justin
Kaiser, Marcus
Thesen, Thomas
Ruths, Justin
Optimal control based seizure abatement using patient derived connectivity
description Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations as opposed to low amplitude irregular oscillations in the non-seizure state. Active brain stimulation has been proposed as a method to terminate seizures prematurely, however, a general and widely-applicable approach to optimal stimulation protocols is still lacking. In this study we use a computational model of epileptic spike-wave dynamics to evaluate the effectiveness of a pseudospectral method to simulated seizure abatement. We incorporate brain connectivity derived from magnetic resonance imaging of a subject with idiopathic generalized epilepsy. We find that the pseudospectral method can successfully generate time-varying stimuli that abate simulated seizures, even when including heterogeneous patient specific brain connectivity. The strength of the stimulus required varies in different brain areas. Our results suggest that seizure abatement, modeled as an optimal control problem and solved with the pseudospectral method, offers an attractive approach to treatment for in vivo stimulation techniques. Further, if optimal brain stimulation protocols are to be experimentally successful, then the heterogeneity of cortical connectivity should be accounted for in the development of those protocols and thus more spatially localized solutions may be preferable.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Taylor, Peter N.
Thomas, Jijju
Sinha, Nishant
Dauwels, Justin
Kaiser, Marcus
Thesen, Thomas
Ruths, Justin
format Article
author Taylor, Peter N.
Thomas, Jijju
Sinha, Nishant
Dauwels, Justin
Kaiser, Marcus
Thesen, Thomas
Ruths, Justin
author_sort Taylor, Peter N.
title Optimal control based seizure abatement using patient derived connectivity
title_short Optimal control based seizure abatement using patient derived connectivity
title_full Optimal control based seizure abatement using patient derived connectivity
title_fullStr Optimal control based seizure abatement using patient derived connectivity
title_full_unstemmed Optimal control based seizure abatement using patient derived connectivity
title_sort optimal control based seizure abatement using patient derived connectivity
publishDate 2015
url https://hdl.handle.net/10356/106049
http://hdl.handle.net/10220/26113
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